{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most examples work across multiple plotting backends, this example is also available for:\n",
    "\n",
    "* [Matplotlib - autompg_violins](../matplotlib/autompg_violins.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import holoviews as hv\n",
    "from holoviews import dim\n",
    "\n",
    "from  bokeh.sampledata.autompg import autompg\n",
    "hv.extension('bokeh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Declaring data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "violin = hv.Violin(autompg, ('yr', 'Year'), ('mpg', 'Miles per Gallon')).redim.range(mpg=(8, 45))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "violin.opts(height=500, width=900, violin_fill_color=dim('Year').str(), cmap='Set1')"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python",
   "pygments_lexer": "ipython3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
